Soil assessment in Denmark: Towards soil functional mapping and beyond

Autor: Lucas Carvalho Gomes, Amélie Marie Beucher, Anders Bjørn Møller, Bo V. Iversen, Christen Duus Børgesen, Diana Vigah Adetsu, Gasper Laurent Sechu, Goswin Johann Heckrath, Julian Koch, Kabindra Adhikari, Maria Knadel, Mathieu Lamandé, Mette Balslev Greve, Niels H. Jensen, Sebastian Gutierrez, Thomas Balstrøm, Triven Koganti, Yannik Roell, Yi Peng, Mogens Humlekrog Greve

Publikováno v: Frontiers in Soil Science, Vol 3 (2023)

Soil provides essential ecosystem services sustaining and improving human life, but mapping soil functions is an ongoing challenge. Denmark has a long history of carrying out soil assessments − originally in order to determine tax revenues for the

Externí odkaz: https://doaj.org/article/1d3da117e14f4ab39c8793d8d5f7ebd5

Parameterization of two‐dimensional approaches in HYDRUS‐2D: Part 2. Solute transport at the field and column scale

Autor: Ioannis Varvaris, Bo V. Iversen, Zampela Pittaki-Chrysodonta, Christen Duus Børgesen

Publikováno v: Varvaris, I, Pittaki-Chrysodonta, Z, Børgesen, C D & Iversen, B V 2021, ' Parameterization of two-dimensional approaches in HYDRUS-2D : Part 2. Solute transport at the field and column scale ', Soil Science Society of America Journal, vol. 85, no. 5, pp. 1496-1518 . https://doi.org/10.1002/saj2.20262

In this study, a tracer field experiment was conducted to study the temporal dynamics of bromide movement in a loamy tile-drained agricultural landscape. Moreover, tritium leaching experiments were performed on undisturbed soil columns from the same

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9d16e004ae322207d5a43b5145c0531
https://doi.org/10.1002/saj2.20262

Using machine learning to predict optimal electromagnetic induction instrument configurations for characterizing the shallow subsurface

Autor: Kim Madsen van't Veen, Ty Paul Andrew Ferré, Bo Vangsø Iversen, Christen Duus Børgesen

Publikováno v: van't Veen, K M, Ferré, T P A, Iversen, B V & Børgesen, C D 2022, ' Using machine learning to predict optimal electromagnetic induction instrument configurations for characterizing the shallow subsurface ', Hydrology and Earth System Sciences, vol. 26, no. 1, pp. 55-70 . https://doi.org/10.5194/hess-26-55-2022
Hydrology and Earth System Sciences, Vol 26, Pp 55-70 (2022)

Electromagnetic induction (EMI) is used widely for hydrological and other environmental studies. The apparent electrical conductivity (ECa), which can be mapped efficiently with EMI, correlates with a variety of important soil attributes. EMI instrum

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2b2d14b2ba88855c27eaec76f5cbba5
https://pure.au.dk/portal/da/publications/using-machine-learning-to-predict-optimal-electromagnetic-induction-instrument-configurations-for-characterizing-the-shallow-subsurface(086c7560-b297-4753-bb4b-584939e8a0ef).html

Impacts of controlled drainage during winter on the physiology and yield of winter wheat in Denmark

Autor: Mathias Neumann Andersen, Majken M. Deichmann, Ingrid K. Thomsen, Christen Duus Børgesen

Publikováno v: Deichmann, M M, Andersen, M N, Thomsen, I K & Børgesen, C D 2019, ' Impacts of controlled drainage during winter on the physiology and yield of winter wheat in Denmark ', Agricultural Water Management, vol. 216, pp. 118-126 . https://doi.org/10.1016/j.agwat.2019.01.013

Controlled Drainage (CD) is a measure designed to lower N-leaching from agricultural fields. However, raising the drainage depth in fields creating partially waterlogged conditions can have negative impacts on the yield and development of winter cere

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90fd80bc342cbf6f8e74872c996a6797
https://doi.org/10.1016/j.agwat.2019.01.013

Using Machine Learning to Predict Optimal Electromagnetic Induction Instrument Configurations for Characterizing the Root Zone

Autor: Bo V. Iversen, Kim Madsen van't Veen, Christen Duus Børgesen, Ty P. A. Ferré

Electromagnetic induction (EMI) is used widely for hydrological and other environmental studies. The apparent electrical conductivity (ECa), which can be mapped efficiently with EMI, correlates with a variety of important soil attributes. EMI instrum

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9a2a9b41cf0f982361de9056dd1d066
https://doi.org/10.5194/hess-2021-201